Triple
T29078985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Israel 2004 |
E733920
|
entity |
| Predicate | winnerInternationalPageant |
P156475
|
FINISHED |
| Object | Miss Universe 2004 |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Miss Universe 2004 | Statement: [Miss Israel 2004, winnerInternationalPageant, Miss Universe 2004]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerInternationalPageant Context triple: [Miss Israel 2004, winnerInternationalPageant, Miss Universe 2004]
-
A.
notableInternationalPageant
Indicates that the subject is a notable or significant international beauty pageant.
-
B.
competitionWinnerFor
chosen
Indicates that an entity is the winner of a specified competition or contest.
-
C.
winnerDam
Indicates that the subject entity is the dam (mother) of an offspring that has won a specified race or competition.
-
D.
winnerCountry
Indicates the country that achieved first place or victory in a given competition, event, or contest.
-
E.
womenAllAroundChampion
Indicates that women are present surrounding or on all sides of the champion.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 28, 2026, 10:52 a.m.